Using Systems Engineering and Implementation Science to Design an Implementation Package for Preoperative Comprehensive Geriatric Assessment Among Older Adults Having Major Abdominal Surgery: Protocol for a 3-Phase Study

BACKGROUND

Older Americans, a growing segment of the population, have an increasing need for surgical services, and they experience a disproportionate burden of postoperative complications compared to their younger counterparts. A preoperative comprehensive geriatric assessment (pCGA) is recommended to reduce risk and improve surgical care delivery for this population, which has been identified as vulnerable. The pCGA optimizes multiple chronic conditions and factors commonly overlooked in routine preoperative planning, including physical function, polypharmacy, nutrition, cognition, mental health, and social and environmental support. The pCGA has been shown to decrease postoperative morbidity, mortality, and length of stay in a variety of surgical specialties. Although national guidelines recommend the use of the pCGA, a paucity of strategic guidance for implementation limits its uptake to a few academic medical centers. By applying implementation science and human factors engineering methods, this study will provide the necessary evidence to optimize the implementation of the pCGA in a variety of health care settings.

OBJECTIVE

The purpose of this paper is to describe the study protocol to design an adaptable, user-centered pCGA implementation package for use among older adults before major abdominal surgery.

METHODS

This protocol uses systems engineering methods to develop, tailor, and pilot-test a user-centered pCGA implementation package, which can be adapted to community-based hospitals in preparation for a multisite implementation trial. The protocol is based upon the National Institutes of Health Stage Model for Behavioral Intervention Development and aligns with the goal to develop behavioral interventions with an eye to real-world implementation. In phase 1, we will use observation and interviews to map the pCGA process and identify system-based barriers and facilitators to its use among older adults undergoing major abdominal surgery. In phase 2, we will apply user-centered design methods, engaging health care providers, patients, and caregivers to co-design a pCGA implementation package. This package will be applicable to a diverse population of older patients undergoing major abdominal surgery at a large academic hospital and an affiliate community site. In phase 3, we will pilot-test and refine the pCGA implementation package in preparation for a future randomized controlled implementation-effectiveness trial. We anticipate that this study will take approximately 60 months (April 2023-March 2028).

RESULTS

This study protocol will generate (1) a detailed process map of the pCGA; (2) an adaptable, user-centered pCGA implementation package ready for feasibility testing in a pilot trial; and (3) preliminary pilot data on the implementation and effectiveness of the package. We anticipate that these data will serve as the basis for future multisite hybrid implementation-effectiveness clinical trials of the pCGA in older adults undergoing major abdominal surgery.

CONCLUSIONS

The expected results of this study will contribute to improving perioperative care processes for older adults before major abdominal surgery.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/59428.

Potential Impact of an Artificial Intelligence-based Mammography Triage Algorithm on Performance and Workload in a Population-based Screening Sample

OBJECTIVE

To evaluate potential screening mammography performance and workload impact using a commercial artificial intelligence (AI)-based triage device in a population-based screening sample.

METHODS

In this retrospective study, a sample of 2129 women who underwent screening mammograms were evaluated. The performance of a commercial AI-based triage device was compared with radiologists' reports, actual outcomes, and national benchmarks using commonly used mammography metrics. Up to 5 years of follow-up examination results were evaluated in cases to establish benignity. The algorithm sorted cases into groups of "suspicious" and "low suspicion." A theoretical workload reduction was calculated by subtracting cases triaged as "low suspicion" from the sample.

RESULTS

At the default 93% sensitivity setting, there was significant improvement (P <.05) in the following triage simulation mean performance measures compared with actual outcome: 45.5% improvement in recall rate (13.4% to 7.3%; 95% CI, 6.2-8.3), 119% improvement in positive predictive value (PPV) 1 (5.3% to 11.6%; 95% CI, 9.96-13.4), 28.5% improvement in PPV2 (24.6% to 31.6%; 95% CI, 24.8-39.1), 20% improvement in sensitivity (83.3% to 100%; 95% CI, 100-100), and 7.2% improvement in specificity (87.2% to 93.5%; 95% CI, 92.4-94.5). A theoretical 62.5% workload reduction was possible. At the ultrahigh 99% sensitivity setting, a theoretical 27% workload reduction was possible. No cancers were missed by the algorithm at either sensitivity.

CONCLUSION

Artificial intelligence-based triage in this simulation demonstrated potential for significant improvement in mammography performance and predicted substantial theoretical workload reduction without any missed cancers.

Caring for Veterans With Depression and Cancer: An Overview for Civilian Nurse Clinicians

PURPOSE

Veterans put their lives on the line to serve our country, but their well-being is often threatened by multifaceted health issues related to military service, including elevated rates of lung cancer and depression. A significant percentage of Veterans have lost faith in mental health care or are unable to breach stigma-related barriers to seek and engage in this care. Veterans' lack of trust can be exacerbated by community mental health clinicians who have had little experience with Veterans and feel inadequately prepared to address their complex needs.

METHOD

The following databases were searched: PubMed, CINAHL Plus with Full Text, and Google Scholar; as well as the U.S. Department of Veterans Affairs website.

RESULTS

Results indicated that 50% of Veterans use civilian health care and perceive that civilian nurses lack knowledge of military culture and related trauma.

CONCLUSION

The current review offers civilian mental health professionals an overview of Veterans' unique issues and provides resources and practical suggestions for helping them overcome barriers to mental health care. [Journal of Psychosocial Nursing and Mental Health Services, xx(x), xx-xx.].

Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions

Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning and natural language processing, and their applications in HNC. The integration of AI with imaging techniques, genomics, and electronic health records is explored, emphasizing its role in early detection, biomarker discovery, and treatment planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, and the need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, and real-time monitoring systems are poised to further advance the field. Addressing these challenges and fostering collaboration among AI experts, clinicians, and researchers is crucial for developing equitable and effective AI applications. The future of AI in HNC holds significant promise, offering potential breakthroughs in diagnostics, personalized therapies, and improved patient outcomes.

Allies, Advocates, and Accomplices in Veterinary Medicine

For those new to the concept of allyship, this article will outline some of the foundation skills of allyship and strategies to overcome common hurdles. For those who consider themselves further along their allyship journey, there is material to encourage more effective or strategic allyship activities. Readers are encouraged to reflect on the different ways they can practice allyship within their own organizations. For leadership and management, we outline why allyship is important in veterinary workplaces and set out some key organization changes that can build inclusive workplaces through allyship.

Mapping the migrant diagnostic radiographers in the UK: A national survey

INTRODUCTION

The international recruitment of healthcare workers remains a UK strategy to manage workforce gaps and maintain service delivery. Although not a new phenomenon, this has been exacerbated by chronic shortages. There is a need to profile the current international recruits and identify individual motivators to understand the opportunities for future recruitment and retention initiatives.

METHOD

A UK-wide electronic survey was conducted using the Jisc platform. The survey was promoted using social media and researcher networks. Eligibility criteria were diagnostic radiographers, internationally educated, and currently working in the UK.

RESULTS

226 responses were received. Most were working in England (90.7%) and 58.0% were under 35 years of age. The majority had migrated having moved to the UK since 2020 (63.7%) and the main drivers were career and/or training opportunities. Initial education was in 30 different countries, the highest number originating from Africa and Asia, with a median of 6 years post-qualification experience (IQR 4-11yrs). Despite experience, most were employed in band 5 (n = 72) or band 6 posts (n = 95). 56% had postgraduate qualifications on entry and a third had undertaken postgraduate study in the UK.

CONCLUSION

Based on the survey responses, the profile of internationally recruited diagnostic radiographers is relatively young but with pre-migration experience originating all over the globe. They are motivated to work in the UK particular for career progression opportunities.

IMPLICATIONS FOR PRACTICE

This study provides an insight into the motivations, demographics and employment patterns of internationally recruited radiographers working in the UK.

Facing the climate change: Is radiotherapy as green as we would like? A systematic review

PURPOSE

To focus on the ecological footprint of radiotherapy (RT), on opportunities for sustainable practices, on future research directions.

METHODS

Different databases were interrogated using the following terms: Carbon Footprint, Sustainab*, Carbon Dioxide, Radiotherapy, and relative synonyms.

RESULTS

931 records were retrieved; 15 reports were included in the review. Eight main thematic areas have been identified. Nine research works analyzed the environmental impact of photon-based external beam RT. Particle therapy was the subject of one work. Other thematic areas were brachytherapy, intra-operative RT, telemedicine, travel-related issues, and the impact of COVID-19.

CONCLUSION

This review demonstrates the strong interest in identifying novel strategies for a more environmentally friendly RT and serves as a clarion call to unveil the environmental impact of carbon footprints entwined with radiation therapy. Future research should address current gaps to guide the transition towards greener practices, reducing the environmental footprint and maintaining high-quality care.

Qualitative study of UK health and care professionals to determine resources and processes that can support actions to improve quality of data used to address and monitor health inequalities

INTRODUCTION

Health inequalities in the UK are investigated and addressed by analysing data across socioeconomic factors, geography and specific characteristics, including those protected under law. It is acknowledged that the quality of data underpinning these analyses can be improved. The objective of this work was to gain insights from professionals working across the health and care sector in England into the type(s) of resource(s) that can be instrumental in implementing mechanisms to improve data quality into practice.

DESIGN

Qualitative study based on semistructured interviews involving health and care professionals.

SETTING

England.

PARTICIPANTS

A total of 16 professionals, mainly from the East of England.

RESULTS

Awareness of mechanisms that could be put in place to improve quality of data related to health inequalities was high among interviewees. However, logistical (eg, workforce time, capacity and funding) as well as data usage (eg, differences in data granularity, information governance structures) barriers impacted on implementation of many mechanisms. Participants also acknowledged that concepts and priorities around health inequalities can vary across the system. While there are resources already available that can aid in improving data quality, finding them and ensuring they are suited to needs was time-consuming. Our analysis indicates that resources to support the creation of a shared understanding of what health inequalities are and share knowledge of specific initiatives to improve data quality between systems, organisations and individuals are useful.

CONCLUSIONS

Different resources are needed to support actions to improve quality of data used to investigate heath inequalities. These include those aimed at raising awareness about mechanisms to improve data quality as well as those addressing system-level issues that impact on implementation. The findings of this work provide insights into actionable steps local health and care services can take to improve the quality of data used to address health inequalities.

Supporting appropriate use of extended dual antiplatelet therapy post-myocardial infarction based on an innovative 12-month ticagrelor virtual service

Purpose

Extended dual antiplatelet therapy (DAPT) with ticagrelor and aspirin is recommended in selected cases after myocardial infarction (MI) but not widely deployed in practice. This study assessed an innovative, cardiology pharmacist-led virtual service for determining eligibility for extended DAPT among patients completing 12 months of initial DAPT in primary care following MI.

Methods

Within this model, potentially eligible individuals are reviewed virtually by a cardiology pharmacist for suitability for extended DAPT with reduced-dose ticagrelor [60 mg twice daily (BD)] for up to 3 years. Eligibility is guided by the PEGASUS-TIMI 54 trial criteria (aged ≥50 years and having ≥1 high-risk feature for further ischaemic events). This is balanced against potential ineligibility driven primarily by bleeding risk, assessed using PRECISE-DAPT score. The final recommendation is sent to primary care to action. The present work is a retrospective evaluation of patients referred to the service between July 2018 and December 2021.

Results

A total of 200 patients were included [n = 131 (65.5%) male; mean age: 69.4 ± 9.5 years]. Of these, 79 (39.5%) were recommended for extended DAPT based on the balance of risks for further ischaemic events vs. bleeding. Sixty-three patients on high-dose DAPT (ticagrelor 90 mg BD)-which is inappropriate beyond 12 months-were reassigned to reduced-dose DAPT or aspirin monotherapy.

Conclusions

This virtual clinic played a key role in medicines optimisation, enabling appropriate patients to benefit from extended DAPT while offsetting bleeding risk. The model could be adapted locally for use elsewhere.

Trustworthy and ethical AI-enabled cardiovascular care: a rapid review

BACKGROUND

Artificial intelligence (AI) is increasingly used for prevention, diagnosis, monitoring, and treatment of cardiovascular diseases. Despite the potential for AI to improve care, ethical concerns and mistrust in AI-enabled healthcare exist among the public and medical community. Given the rapid and transformative recent growth of AI in cardiovascular care, to inform practice guidelines and regulatory policies that facilitate ethical and trustworthy use of AI in medicine, we conducted a literature review to identify key ethical and trust barriers and facilitators from patients' and healthcare providers' perspectives when using AI in cardiovascular care.

METHODS

In this rapid literature review, we searched six bibliographic databases to identify publications discussing transparency, trust, or ethical concerns (outcomes of interest) associated with AI-based medical devices (interventions of interest) in the context of cardiovascular care from patients', caregivers', or healthcare providers' perspectives. The search was completed on May 24, 2022 and was not limited by date or study design.

RESULTS

After reviewing 7,925 papers from six databases and 3,603 papers identified through citation chasing, 145 articles were included. Key ethical concerns included privacy, security, or confidentiality issues (n = 59, 40.7%); risk of healthcare inequity or disparity (n = 36, 24.8%); risk of patient harm (n = 24, 16.6%); accountability and responsibility concerns (n = 19, 13.1%); problematic informed consent and potential loss of patient autonomy (n = 17, 11.7%); and issues related to data ownership (n = 11, 7.6%). Major trust barriers included data privacy and security concerns, potential risk of patient harm, perceived lack of transparency about AI-enabled medical devices, concerns about AI replacing human aspects of care, concerns about prioritizing profits over patients' interests, and lack of robust evidence related to the accuracy and limitations of AI-based medical devices. Ethical and trust facilitators included ensuring data privacy and data validation, conducting clinical trials in diverse cohorts, providing appropriate training and resources to patients and healthcare providers and improving their engagement in different phases of AI implementation, and establishing further regulatory oversights.

CONCLUSION

This review revealed key ethical concerns and barriers and facilitators of trust in AI-enabled medical devices from patients' and healthcare providers' perspectives. Successful integration of AI into cardiovascular care necessitates implementation of mitigation strategies. These strategies should focus on enhanced regulatory oversight on the use of patient data and promoting transparency around the use of AI in patient care.

Artificial Intelligence and cancer: Profile of registered clinical trials

Artificial Intelligence (AI) has made significant strides due to advancements in processing algorithms and data availability. Recent years have shown a resurgence in AI, driven by breakthroughs in deep machine learning. AI has attracted particular interest in the medical sector, especially in the field of personalized medicine, which for example uses large-scale genomic and molecular data to predict individual patient treatment responses. The applications of AI in disease diagnosis, monitoring, and treatment are expanding rapidly, leading to a growing number of registered trials. Therefore, this study aimed to identify and evaluate clinical trials registered between January 1st 2016, and September 30th 2023 that connect AI and cancer. Our findings show that the number of clinical trials linking AI with cancer research has grown significantly compared to other diseases, with colorectal and breast tumour types showing the highest number of registered trials. The most frequent intervention was disease diagnosis and monitoring. Regarding countries, China and the United States hold the highest numbers of registered trials. In conclusion, oncology is a field with a great interest in AI, where the developed countries are leading the studies in this field. Unfortunately, developing countries are still crawling in this aspect and government policies should be made to improve that area.

Needs Assessment for a Leadership Course in Saudi Medical Schools: The Student Perspective

Introduction

Leaders in healthcare no longer need to hold formal management positions; instead, leadership is perceived to be the responsibility of all healthcare professionals. Despite changes in curricula and teaching design, however, this review of the content taught in medical colleges in Saudi Arabia reveals a lack of leadership and a failure to equip young graduates to compete on the global stage. Medical students need leadership skills for patient care, cooperation, and navigating the complex healthcare system. Clinical management skills in hospitals require these talents also. The complexity of healthcare and the impact healthcare executives have on people's lives highlight the importance of these skills. Thus, healthcare practitioners must develop non-technical skills like proactivity, motivation, and change management to lead across professional boundaries and negotiate the increasingly complex healthcare landscape.

Methods

This cross-sectional study combines a quantitative approach with a self-administered questionnaire-based survey. The sampling procedure is a non-probability convenience technique, adapted for 700 male and female undergraduate medical students from four medical colleges.

Results

Of the students, 75.46% had minimal leadership experience and 22.69% had some leadership experience; 3.02% of 464 students considered themselves highly experienced in leadership.

Conclusion

As the needs assessment and other relevant factors show, leadership should be introduced as a skilled subject. There will always be a growing demand for competent medical graduates, who are capable of becoming future leaders. Although elementary leadership concepts remain fundamentally the same, curricular development must focus on the needs of society and stakeholders.

The accuracy of deep learning models for diagnosing maxillary fungal ball rhinosinusitis

PURPOSE

To assess the accuracy of deep learning models for the diagnosis of maxillary fungal ball rhinosinusitis (MFB) and to compare the accuracy, sensitivity, specificity, precision, and F1-score with a rhinologist.

METHODS

Data from 1539 adult chronic rhinosinusitis (CRS) patients who underwent paranasal sinus computed tomography (CT) were collected. The overall dataset consisted of 254 MFB cases and 1285 non-MFB cases. The CT images were constructed and labeled to form the deep learning models. Seventy percent of the images were used for training the deep-learning models, and 30% were used for testing. Whole image analysis and instance segmentation analysis were performed using three different architectures: MobileNetv3, ResNet50, and ResNet101 for whole image analysis, and YOLOv5X-SEG, YOLOv8X-SEG, and YOLOv9-C-SEG for instance segmentation analysis. The ROC curve was assessed. Accuracy, sensitivity (recall), specificity, precision, and F1-score were compared between the models and a rhinologist. Kappa agreement was evaluated.

RESULTS

Whole image analysis showed lower precision, recall, and F1-score compared to instance segmentation. The models exhibited an area under the ROC curve of 0.86 for whole image analysis and 0.88 for instance segmentation. In the testing dataset for whole images, the MobileNet V3 model showed 81.00% accuracy, 47.40% sensitivity, 87.90% specificity, 66.80% precision, and a 67.20% F1 score. Instance segmentation yielded the best evaluation with YOLOv8X-SEG showing 94.10% accuracy, 85.90% sensitivity, 95.80% specificity, 88.90% precision, and an 89.80% F1-score. The rhinologist achieved 93.5% accuracy, 84.6% sensitivity, 95.3% specificity, 78.6% precision, and an 81.5% F1-score.

CONCLUSION

Utilizing paranasal sinus CT imaging with enhanced localization and constructive instance segmentation in deep learning models can be the practical promising deep learning system in assisting physicians for diagnosing maxillary fungal ball.

Communication during telemedicine consultations in general practice: perspectives from general practitioners and their patients

BACKGROUND

Telemedicine allows delivery of healthcare to occur between parties that are not in the same location. As telemedicine users are not co-present, effective communication methods are crucial to the delivery and reception of information. The aim of this study was to explore perspectives of general practitioners (GPs) and patients on the interactional components of telemedicine consultations.

METHODS

Semi-structured qualitative interviews were held with telemedicine users; 15 GPs and nine patients self-selected from a larger telemedicine study. Participants were asked about their preparation for telemedicine consultations, conducting telemedicine consultations and post-consultation activities. Deidentified transcripts from the interviews were analysed thematically.

RESULTS

GPs and patients discussed factors they used to decide whether a consultation would be best conducted by telemedicine or in-person; the condition to be discussed, the existing doctor-patient relationship and whether physical examination was required. Participants also described how they prepared for their telemedicine consultations, gathering relevant documents, and reading previous notes. Participants described strategies they employed to optimise the telemedicine interaction; improving conversational flow and building rapport, as well as difficulties they experienced when trying to provide and receive care via telemedicine.

CONCLUSIONS

Patient factors including health literacy and familiarity with technology affect the transfer of information shared during telemedicine consultations and consideration of these factors when choosing patients for telemedicine is required. Many GPs and patients have innate communication skills to effectively deliver and receive care through telemedicine. However, they may not be aware of these subconscious techniques to use to optimise telemedicine consultations. Communication training could be delivered to increase conversational flow, build rapport, and establish safety netting.

Attitudes and perceptions of Chinese oncologists towards artificial intelligence in healthcare: a cross-sectional survey

Background

Artificial intelligence (AI) is transforming healthcare, yet little is known about Chinese oncologists' attitudes towards AI. This study investigated oncologists' knowledge, perceptions, and acceptance of AI in China.

Methods

A cross-sectional online survey was conducted among 228 oncologists across China. The survey examined demographics, AI exposure, knowledge and attitudes using 5-point Likert scales, and factors influencing AI adoption. Data were analyzed using descriptive statistics and chi-square tests.

Results

Respondents showed moderate understanding of AI concepts (mean 3.39/5), with higher knowledge among younger oncologists. Only 12.8% used ChatGPT. Most (74.13%) agreed AI is beneficial and could innovate healthcare, 52.19% respondents expressed trust in AI technology. Acceptance was cautiously optimistic (mean 3.57/5). Younger respondents (∼30) show significantly higher trust (p = 0.004) and acceptance (p = 0.009) of AI compared to older respondents, while trust is significantly higher among those with master's or doctorate vs. bachelor's degrees (p = 0.032), and acceptance is higher for those with prior IT experience (p = 0.035).Key drivers for AI adoption were improving efficiency (85.09%), quality (85.53%), reducing errors (84.65%), and enabling new approaches (73.25%).

Conclusions

Chinese oncologists are open to healthcare AI but remain prudently optimistic given limitations. Targeted education, especially for older oncologists, can facilitate AI implementation. AI is largely welcomed for its potential to augment human roles in enhancing efficiency, quality, safety, and innovations in oncology practice.

Clinician perspectives and recommendations regarding design of clinical prediction models for deteriorating patients in acute care

BACKGROUND

Successful deployment of clinical prediction models for clinical deterioration relates not only to predictive performance but to integration into the decision making process. Models may demonstrate good discrimination and calibration, but fail to match the needs of practising acute care clinicians who receive, interpret, and act upon model outputs or alerts. We sought to understand how prediction models for clinical deterioration, also known as early warning scores (EWS), influence the decision-making of clinicians who regularly use them and elicit their perspectives on model design to guide future deterioration model development and implementation.

METHODS

Nurses and doctors who regularly receive or respond to EWS alerts in two digital metropolitan hospitals were interviewed for up to one hour between February 2022 and March 2023 using semi-structured formats. We grouped interview data into sub-themes and then into general themes using reflexive thematic analysis. Themes were then mapped to a model of clinical decision making using deductive framework mapping to develop a set of practical recommendations for future deterioration model development and deployment.

RESULTS

Fifteen nurses (n = 8) and doctors (n = 7) were interviewed for a mean duration of 42 min. Participants emphasised the importance of using predictive tools for supporting rather than supplanting critical thinking, avoiding over-protocolising care, incorporating important contextual information and focusing on how clinicians generate, test, and select diagnostic hypotheses when managing deteriorating patients. These themes were incorporated into a conceptual model which informed recommendations that clinical deterioration prediction models demonstrate transparency and interactivity, generate outputs tailored to the tasks and responsibilities of end-users, avoid priming clinicians with potential diagnoses before patients were physically assessed, and support the process of deciding upon subsequent management.

CONCLUSIONS

Prediction models for deteriorating inpatients may be more impactful if they are designed in accordance with the decision-making processes of acute care clinicians. Models should produce actionable outputs that assist with, rather than supplant, critical thinking.

Rate and sociodemographic correlates of depression, anxiety, and stress among domestic and overseas medical students: A cross-sectional observation from a private medical college in Bangladesh

Background

Depression, anxiety, and stress are the commonly encountered mental health conditions among medical students. Overseas environment may add additional burden to the existing environment. However, comparison of the rate and associated factors of depression, anxiety, stress among domestic and overseas students has not been attempted in Bangladesh. We aimed to assess the rate and associated factors of depression, anxiety, stress among domestic and overseas medical students in the country.

Methods

This cross-sectional study was conducted among 360 undergraduate medical students in 2021. Data were collected by self-reporting instruments by a stratified random sampling method by the Depression, Anxiety, and Stress Scale-21 scale. Bivariable and multivariable binary logistic regression analyses were done by computing crude odds ratio and adjusted odds ratio with 95% confidence interval to identify the associated factors.

Results

Among the 360 undergraduate medical students, 181 were domestic and 179 overseas ones. 44.8% of domestic students reported depressive symptoms, 45.3% reported anxiety symptoms, and 33.1% reported stress. On the other hand, half of overseas students experienced depression (50.3%) and anxiety (52.5%), and 41.3% experienced stress. Female medical students were found vulnerable for developing depression, anxiety, and stress than males.

Conclusions

The study revealed higher rates of depression, anxiety, and stress among overseas undergraduate medical students enrolled in a private medical school of Bangladesh. Private medical college authorities could consider special services for overseas students to ensure adequate psychosocial support.

Interventions to minimise hospital winter pressures related to discharge planning and integrated care: a rapid mapping review of UK evidence

Background

Winter pressures are a familiar phenomenon within the National Health Service and represent the most extreme of many regular demands placed on health and social care service provision. This review focuses on a part of the pathway that is particularly problematic: the discharge process from hospital to social care and the community. Although studies of discharge are plentiful, we identified a need to focus on identifying interventions and initiatives that are a specific response to 'winter pressures'. This mapping review focuses on interventions or initiatives in relation to hospital winter pressures in the United Kingdom with either discharge planning to increase smart discharge (both a reduction in patients waiting to be discharged and patients being discharged to the most appropriate place) and/or integrated care.

Methods

We conducted a mapping review of United Kingdom evidence published 2018-22. Initially, we searched MEDLINE, Health Management Information Consortium, Social Care Online, Social Sciences Citation Index and the King's Fund Library to find relevant interventions in conjunction with winter pressures. From these interventions we created a taxonomy of intervention types and a draft map. A second broader stage of searching was then undertaken for named candidate interventions on Google Scholar (Google Inc., Mountain View, CA, USA). For each taxonomy heading, we produced a table with definitions, findings from research studies, local initiatives and systematic reviews and evidence gaps.

Results

The taxonomy developed was split into structural, changing staff behaviour, changing community provision, integrated care, targeting carers, modelling and workforce planning. The last two categories were excluded from the scope. Within the different taxonomy sections we generated a total of 41 headings. These headings were further organised into the different stages of the patient pathway: hospital avoidance, alternative delivery site, facilitated discharge and cross-cutting. The evidence for each heading was summarised in tables and evidence gaps were identified.

Conclusions

Few initiatives identified were specifically identified as a response to winter pressures. Discharge to assess and hospital at home interventions are heavily used and well supported by the evidence but other responses, while also heavily used, were based on limited evidence. There is a lack of studies considering patient, family and provider needs when developing interventions aimed at improving delayed discharge. Additionally, there is a shortage of studies that measure the longer-term impact of interventions. Hospital avoidance and discharge planning are whole-system approaches. Considering the whole health and social care system is imperative to ensure that implementing an initiative in one setting does not just move the problem to another setting.

Limitations

Time limitations for completing the review constrained the period available for additional searches. This may carry implications for the completeness of the evidence base identified.

Future work

Further research to consider a realist review that views approaches across the different sectors within a whole system evaluation frame.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR130588) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 31. See the NIHR Funding and Awards website for further award information.

Transforming medical education: the impact of innovations in technology and medical devices

INTRODUCTION

The rapid advancement of technology and the integration of innovative medical devices are significantly transforming medical education. This review examines the impact of these changes and the importance of adapting educational strategies to leverage these advancements.

AREAS COVERED

This narrative review employs a qualitative approach. From an initial pool of 294 articles, researchers conducted independent screenings and identified 134 studies relevant to innovations in technology and their impact on medical education. Following a comprehensive review and consensus, studies deemed to be of low relevance were excluded, resulting in a final selection of 74 articles. An expert panel discussion was held, and the study concludes with a final section that presents the findings and offers brief, clear recommendations.

EXPERT OPINION

This study indicates that the utilization of Innovative medical technologies has the potential to enhance learning outcomes. The use of simulations allows students to engage in hands-on practice without risking patient harm. Mobile devices afford students uninterrupted access to educational resources, thereby enabling efficient learning. Artificial intelligence (AI) has the potential to personalize education, enhance diagnostic skills, and foster critical thinking. Further research in this field has the potential to yield significant insights.

Virtual Reality in Cancer Care: Enhancing Knowledge and Reducing Anxiety about Chemotherapy among Patients and Caregivers

Virtual reality (VR) technology has evolved from entertainment to significant applications in healthcare and education. Despite its potential, there is limited research on the role of VR in cancer care. This study investigates VR's ability to simulate the chemotherapy process, aiming to enhance patients' knowledge and mitigate anxiety associated with chemotherapy. Utilizing a two-arm, mixed-methods pre/post-survey design, the study measured changes in patients' anxiety and knowledge before and after exposure to a VR simulation. Participants (n = 267) engaged with VR simulations or interactive 360-degree videos depicting the chemotherapy process. Data analyses revealed a significant median increase in chemotherapy knowledge post-exposure to the VR content (z = 12.511, p < 0.001). Demographic factSors significantly influenced perceptions of VR realism and usefulness (p < 0.05). Additionally, VR exposure was correlated with reduced anxiety levels and improved treatment expectations (p < 0.05). Participants with higher post-understanding chemotherapy scores considered VR a useful tool for managing anxiety about chemotherapy and recommended VR for other medical procedures (p < 0.001). These findings underscore VR technology's potential as a valuable tool in cancer treatment, suggesting it can enhance patient education and reduce anxiety, thereby improving patient outcomes during cancer therapy.

Advancements in AI based healthcare techniques with FOCUS ON diagnostic techniques

Since the past decade, the interest towards more precise and efficient healthcare techniques with special emphasis on diagnostic techniques has increased. Artificial Intelligence has proved to be instrumental in development of various such techniques. The various types of AI like ML, NLP, RPA etc. are being used, which have streamlined and organised the Electronic Health Records (EHR) along with aiding the healthcare provider with decision making and sample and data analysis. This article also deals with the 3 major categories of diagnostic techniques - Imaging based, Pathology based and Preventive diagnostic techniques and what all changes and modifications were brought upon them, due to use of AI. Due to such a high demand, the investment in AI based healthcare techniques has increased substantially, with predicted market size of almost 188 billon USD by 2030. In India itself, AI in healthcare is expected to raise the GDP by 25 billion USD by 2028. But there are also several challenges associated with this like unavailability of quality data, black box issue etc. One of the major challenges is the ethical considerations and issues during use of medical records as it is a very sensitive document. Due to this, there is several trust issues associated with adoption of AI by many organizations. These challenges have also been discussed in this article. Need for further development in the AI based diagnostic techniques is also done in the article. Alongside, the production of such techniques and devices which are easy to use and simple to incorporate into the daily workflows have immense scope in the upcoming times. The increasing scope of Clinical Decision Support System, Telemedicine etc. make AI a promising field in the healthcare and diagnostics arena. Concluding the article, it can be said that despite the presence of various challenges to the implementation and usage, the future prospects for AI in healthcare is immense and work needs to be done in order to ensure the availability of resources for same so that high level of accuracy can be achieved and better health outcomes can be provided to patients. Ethical concerns need to be addressed for smooth implementation and to reduce the burden of the developers, which has been discussed in this narrative review article.

Addressing hidden tensions and grey areas of general practice: a qualitative study of the experiences of newly qualified GPs attending a course on generalist medicine

BACKGROUND

Generalist approaches can help address several challenges facing today's primary care. However, GPs report insufficient support to deliver advanced generalist medicine (AGM) in daily practice, struggling within a healthcare system that imposes strict adherence to single-disease focused guidelines.

AIM

To examine the professional and educational experiences of newly qualified GPs attending a course on AGM to understand how to redesign primary care systems to support their generalist work.

DESIGN AND SETTING

This was a qualitative study focusing on AGM in UK general practice (England), conducted in the context of the research evaluation of an online career development programme on AGM.

METHOD

We conducted 36 interviews and six focus groups with newly qualified GPs attending an online career development programme on AGM, and analysed data using framework analysis.

RESULTS

Three tensions experienced by the participants were identified: tension between realistic and idealistic practice; tension between different decision-making paradigms; and tension in the formation of the GPs' professional identities. These were owing to grey areas of practice deeply rooted in primary care systems - namely areas of work not adequately addressed by current education and service design.

CONCLUSION

Our findings have implications for tackling the general practice workforce crisis, highlighting that solutions targeting individual problems will not suffice by themselves. By making visible the grey areas of everyday general practice, we describe the changes needed to target tensions as described by the GPs in this study to ultimately enable, enhance and make visible the complex work of generalist medicine.

Improving the Accuracy of the Gynaecology Handover Process: An Effective Quality Improvement Project at a University Hospital in the United Kingdom

Objectives The objective of this study was to introduce a new system of handover in the gynaecology department and ensure its effectiveness with dynamic improvement measures. This was launched as a quality improvement project in a district general hospital in the United Kingdom. The primary aim was to start and consolidate a new system of a separate gynaecology handover in the presence of consultants, registrars (incoming and outgoing), senior house officers (incoming and outgoing) and gynaecology nurses. Design The strategy for consolidation included a daily quality review on the basis of a fixed proforma, identifying the obstacles faced, and improvising dynamic solutions. A new quality check proforma was introduced which took into account: (i) Presence of team members, (ii) Following of proper SBAR (Situation, Background, Assessment, Recommendation) format in the handover, (iii) Updating of patients awaiting surgeries with every detail on the list, (iv) Proper handing over of pending referrals, (v) Mention of sick patients with proper importance, and (vi) Proper handing over of new admissions. A pilot study was done to evaluate the baseline performance of the unit regarding the gynaecology team handover on the basis of the same proforma. The result of the baseline study was noted as the reference. Each day the team receiving the handover was interviewed for the next five months about the quality of each of the parameters on the predesigned proforma and the responses were noted. The answers were designed in binary form (Yes/No). These results were compiled at the end of each month. The result from each individual month was reviewed and the problems were identified and practical solutions were applied. These changes were noted and plotted graphically as a bar diagram. The monthly audit results were tabulated in an Excel sheet (Microsoft Corporation, Redmond, Washington, United States). Results Pilot study results and final month results were compared with the help of the Mcnemar test and statistically significant improvement was noticed in seven out of eleven parameters. There was a steady and gradual improvement in the responses. The possible limitations of the study were also noted at the same time. Conclusion The quality improvement project was highly effective in improving the quality of handover and increased patient safety to a large extent.

Measuring environmentally sustainable health care: a scoping review

Work to reduce environmental pollution from the health system is hampered by an absence of consensus on the definition of environmentally sustainable health care and the relevant measurement needed. This scoping review aims to encourage standardisation across sustainability efforts by examining how environmentally sustainable health care is defined and measured in current literature. We conducted a scoping review to identify candidate publications that included either a definition or description of environmentally sustainable health care or a measurement of the impact of health care on the environment. 328 publications were included in the final analysis. 52 publications included definitions or descriptions of environmentally sustainable health care. Results of the study highlight the heterogeneity in the current definition, measurement, and measurement calculation methods of environmentally sustainable health care in published literature. Work is needed to create more harmonised definitions and measurement to support progress and reduce environmental pollution from health care.

Wearable technology in vascular surgery: Current applications and future perspectives

The COVID-19 pandemic exposed the vulnerabilities of global health care systems, underscoring the need for innovative solutions to meet the demands of an aging population, workforce shortages, and rising physician burnout. In recent years, wearable technology has helped segue various medical specialties into the digital era, yet its adoption in vascular surgery remains limited. This article explores the applications of wearable devices in vascular surgery and explores their potential outlets, such as enhancing primary and secondary prevention, optimizing perioperative care, and supporting surgical training. The integration of artificial intelligence and machine learning with wearable technology further expands its applications, enabling predictive analytics, personalized care, and remote monitoring. Despite the promising prospects, challenges such as regulatory complexities, data security, and interoperability must be addressed. As the digital health movement unfolds, wearable technology could play a pivotal role in reshaping vascular surgery while offering cost-effective, accessible, and patient-centered care.

"A great tool to open your eyes": new graduate physiotherapists' perceptions and use of social media for learning

BACKGROUND

Social media offer opportunities for informal learning and are increasingly adopted by health professionals as learning tools. However, little is known of how new graduate physiotherapists engage with social media for learning.

PURPOSE

This study aimed to explore new graduate physiotherapists' perceptions and use of social media as learning tools during their transition into professional practice.

METHODS

This study used a qualitative general inductive approach. New graduate physiotherapists (n = 16) were recruited through purposive snowball sampling and participated in semi-structured interviews. Data were subjected to a general inductive analytical method.

RESULTS

Four themes were generated: 1) social media as tools for learning; 2) navigating and engaging with social media as a learner; 3) thinking critically about social media; and 4) relevance to practice.

CONCLUSION

New graduate physiotherapists use social media as adjunct learning tools which can be positioned within several frameworks, including the Situated Learning Theory. However, new graduates voice uncertainties regarding information credibility, the importance of critical thinking skills in navigating information, and concerns regarding blurred work-life boundaries. Recommendations are made for research to further understand social media as emerging learning tools, especially for new graduates who are experiencing insufficient workplace support.

Exploring opportunities beyond clinical practice: The need for PA educators

ABSTRACT

Opportunities outside patient care are expanding for physician associates/assistants (PAs). Exploring new roles beyond clinical practice has the potential for improved career fulfillment as clinicians experience increasing levels of burnout and declining satisfaction with patient care. The decision to shift to a nonclinical role may be overwhelming without knowing what positions PAs are qualified to consider. PAs are increasingly found in the fields of healthcare consulting (as medical science liaisons), medical writing, healthcare insurance, research, and academia. With the rapid growth in PA programs, the need for educators is critical and this transition creates an interesting dynamic in which a proficient clinician becomes a novice educator. This article delves into these expectations and provides guidance on making the transition.

Comprehensive review of virtual assistants in vascular surgery

Virtual assistants, broadly defined as digital services designed to simulate human conversation and provide personalized responses based on user input, have the potential to improve health care by supporting clinicians and patients in terms of diagnosing and managing disease, performing administrative tasks, and supporting medical research and education. These tasks are particularly helpful in vascular surgery, where the clinical and administrative burden is high due to the rising incidence of vascular disease, the medical complexity of the patients, and the potential for innovation and care advancement. The rapid development of artificial intelligence, machine learning, and natural language processing techniques have facilitated the training of large language models, such as GPT-4 (OpenAI), which can support the development of increasingly powerful virtual assistants. These tools may support holistic, multidisciplinary, and high-quality vascular care delivery throughout the pre-, intra-, and postoperative stages. Importantly, it is critical to consider the design, safety, and challenges related to virtual assistants, including data security, ethical, and equity concerns. By combining the perspectives of patients, clinicians, data scientists, and other stakeholders when developing, implementing, and monitoring virtual assistants, there is potential to harness the power of this technology to care for vascular surgery patients more effectively. In this comprehensive review article, we introduce the concept of virtual assistants, describe potential applications of virtual assistants in vascular surgery for clinicians and patients, highlight the benefits and drawbacks of large language models, such as GPT-4, and discuss considerations around the design, safety, and challenges associated with virtual assistants in vascular surgery.

Ethical Considerations and Equipoise in Cancer Surgery

The changing landscape of cancer surgery requires ongoing consideration of ethical issues to ensure patient-centered care and fair access to treatments. With technological advancements and the global expansion of surgical interventions, healthcare professionals must navigate complex ethical dilemmas related to patient autonomy, informed consent, and the impact of new technologies on the physician-patient relationship. Additionally, ethical principles and decision-making in oncology, especially in the context of genetic predisposition to breast cancer, highlight the importance of integrating patient knowledge, preferences, and alignment between goals and treatments. As global surgery continues to grow, addressing ethical considerations becomes crucial to reduce disparities in access to surgical interventions and uphold ethical duties in patient care. Furthermore, the rise of digital applications in healthcare, such as digital surgery, requires heightened awareness of the unique ethical issues in this domain. The ethical implications of using artificial intelligence (AI) in robotic surgical training have drawn attention to the challenges of protecting patient and surgeon data, as well as the ethical boundaries that innovation may encounter. These discussions collectively emphasize the complex ethical issues associated with surgical innovation and underscore the importance of upholding ethical standards in the pursuit of progress in the field. In this study, we thoroughly analyzed previous scholarly works on ethical considerations and equipoise in the field of oncological surgery. Our main focus was on the use of AI in this specific context.

Women's Health Hubs: a rapid mixed-methods evaluation

Background

Women's sexual and reproductive health needs are complex and vary across the life course. They are met by a range of providers, professionals and venues. Provision is not well integrated, with inequalities in access. In some areas of the United Kingdom Women's Health Hubs have been established to improve provision, experience and outcomes for women, and to address inequalities and reduce costs. These models were established prior to the national implementation of Women's Health Hubs announced in the English 2022 Women's Health Strategy.

Objective

To explore the 'current state of the art', mapping the United Kingdom landscape, and studying experiences of delivering and using Women's Health Hubs across England, defining key features and early markers of success to inform policy and practice.

Design

A mixed-methods evaluation, comprising three work packages: Mapping the Women's Health Hub landscape and context and developing a definition of Women's Health Hubs, informed by an online national survey of Women's Health Hub leaders, and interviews with regional stakeholders. In-depth evaluation in four hub sites, including interviews with staff and women, focus groups in local communities and documentary analysis. Interviews with national stakeholders and consolidation of findings from work packages 1 and 2. Fieldwork was undertaken from May 2022 to March 2023. The evaluation was initiated prior to the national scale-up of Women's Health Hubs announced in the 2022 Women's Health Strategy.

Results

Most areas of the United Kingdom did not have a Women's Health Hub. Seventeen active services were identified, established between 2001 and 2022. Women's Health Hubs were diverse, predominantly GP-led, with different perspectives of the role and definition of a hub. Women using hubs reported positive experiences, finding services caring and convenient. Implementation facilitators included committed, collaborative leaders working across boundaries, sufficient workforce capacity and a supportive policy context. Challenges included access to funding, commissioning, workforce issues, facilities and equipment, stakeholder engagement and wider system integration, priorities and pressures. Leaders were committed to addressing inequalities, but evidence of impact was still emerging.

Limitations

It was challenging to locate models; therefore, some may have been missed. Data availability limited assessment of impact, including inequalities. Some population groups were not represented in the data, and the evaluation was more provider-oriented. It was not possible to develop a typology of Women's Health Hubs as planned due to heterogeneity in models.

Conclusions

Existing Women's Health Hub models were providing integrated approaches to meet local needs. Many were at an early stage of development. Evidence of system-level impact and costs was still emerging. Women's Health Hubs may widen inequalities if models are more accessible to advantaged groups. The important role of committed leaders in existing 'bottom-up' models may limit scalability and sustainability. Findings suggest that national scale-up will take time and requires funding and that it is necessary to design models according to local needs and resources. In 2023, the Department of Health and Social Care announced funding to establish a Women's Health Hub in every Integrated Care System in England.

Future work

Future evaluation should consider system-level impact and costs, explore unintended consequences and test assumptions.

Funding

This award was funded by the National Institute of Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR135589) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 30. See the NIHR Funding and Awards website for further award information.

The imperative of professionalising healthcare management: A global perspective

Effective healthcare management for addressing complex organisational challenges is crucial for efficient healthcare delivery. Healthcare management involves organising, coordinating, planning and operationalising healthcare services, as well as leading people to ensure the delivery of effective patient care. Healthcare management applies management principles and practices to various healthcare organisations, such as hospitals, functional departments, clinics, cross-functional departments and public health organisations. Recognising a gap in management training, especially for clinicians having managerial responsibilities, is a call for global professionalisation of healthcare management to equip leaders with essential skills. In many healthcare settings across the globe, healthcare management does not always require professional management qualifications. This article advocates for the need for a structured approach towards professionalising healthcare management globally and especially in the Eastern Mediterranean Region (EMR).

Desires and attitudes of outpatients and physicians regarding the use of teleurology during the pandemic: a prospective survey study

OBJECTIVE

It is not known to date how many patients admitted to urology outpatient clinics are willing to use telemedicine. We aimed to investigate knowledge levels and attitudes concerning the utilization of teleurology by patients applying to urology outpatient clinics.

METHODS

This prospective multicentre survey study included 334 patients aged 18-65 years who applied to an urology outpatient clinics. The patients were asked questions about their attitudes and expectations regarding teleurology. Diseases were divided into seven subgroups due to the broad spectrum of diagnoses. Physicians' and patients' opinions on whether it was possible to manage the current medical condition via teleurology were recorded.

RESULTS

69.5% of patients stated that they had sufficient technical skills to use teleurology by themselves for medical examination. 55.4% of patients and 78.4% of physicians responded that the existing complaints were suitable for teleurology. Both patients and physicians deemed genital system diseases and urinary tract infections suitable for teleurology (p<0.001, p<0.001 for physicians, and p<0.001, p<0.001 for patients), whereas urine transport, storage and emptying disorders (p=0.003) and benign prostatic hyperplasia (p=0.029) were deemed to be suitable for teleurology only by the physicians.

CONCLUSION

Our study shows that (i) the majority of our patient population has a telecommunications infrastructure suitable for teleurology, (ii) teleurology has aroused interest among patients, particularly during the pandemic period, and (iii) physicians and patients have high expectations that the problem can be solved with teleurology in suitable patients.

Eco-sustainability in ophthalmology

PURPOSE OF REVIEW

The purpose of this review is to evaluate the current state of eco-sustainability in ophthalmology, highlighting key practices, recent advancements, and areas requiring improvement. This review aims to provide ophthalmologists with a comprehensive overview of sustainable practices that can reduce environmental impact.

RECENT FINDINGS

Recent studies have identified several areas within ophthalmology where sustainable practices can be implemented including multidose eyedrops, adjusting surgical packs, making package inserts available electronically, and reusing surgical instruments. Moreover, there is an increasing emphasis on waste reduction both in the surgical and clinical setting, by decreasing the use of unnecessary materials and implementing more efficient use of recycling programs. Telemedicine has also emerged as a sustainable option, reducing the carbon footprint associated with patient travel. Despite these advancements, significant challenges remain, particularly in balancing the cost and accessibility of sustainable options with traditional practices.

SUMMARY

Eco-sustainability in ophthalmology is gaining momentum as the medical community aims to reduce its environmental impact. While progress has been made, further efforts are required to overcome financial and logistical barriers to widespread implementation. Continued research, education, and policy development are essential to advancing eco-sustainable practices, ensuring that environmental considerations become an integral part of ophthalmic care.

Development of neonatal Apgar scoring training program utilizing contactless hand tracking in immersive virtual reality

BACKGROUND

The rapid and accurate assessment of neonatal asphyxia is critical to preventing potentially fatal outcomes. Therefore, nursing students must acquire the skills to assess newborn conditions immediately after birth and implement appropriate interventions. Virtual reality (VR) simulation education has emerged as a promising tool for nursing education, offering repetitive and customizable clinical training while ensuring patient safety and overcoming spatiotemporal limitations.

AIM

This study investigated the effects of a contactless hand-tracking-based immersive VR neonatal Apgar scoring program, adapted from experiential learning theory.

DESIGN

A non-randomized controlled trial with a pre-post-test, quasi-experimental design was conducted.

SETTINGS

The study was conducted at two nursing schools from July to October 2023.

PARTICIPANTS

Participants comprised nursing students holding bachelor's degrees in nursing, with three or four years of experience and successful completion of a neonatal nursing theory course. Additionally, individuals with at least six months of experience working in a neonatal ward or delivery room before enrolling in nursing school were eligible.

METHODS

The participants were divided into three groups: the VR group (n = 27) received contactless hand-tracking-based immersive VR neonatal Apgar scoring training; the simulation group (n = 28) received face-to-face Apgar scoring simulation training; and the control group (n = 26) received instruction on the Apgar scoring criteria. Changes in scores among the VR, simulation, and control groups were statistically compared using ANOVA with SPSS-WIN 27.0.

RESULTS

The VR group exhibited significant improvements in knowledge, learning satisfaction, self-confidence, immersion, and motivation compared to the simulation and control groups. Moreover, satisfaction was significantly higher in the VR group than in the simulation group.

CONCLUSIONS

The hand-tracking-based immersive VR neonatal Apgar scoring program represents an innovative and effective educational tool, prioritizing the privacy and rights of mothers and infants. It can potentially replace traditional delivery-room clinical training, which is observation-based and limited.

Benefits and Barriers of Using Virtual Reality in Teaching Undergraduate Nursing Students: A Scoping Review

BACKGROUND

Although studies have been conducted using virtual reality (VR) in nursing education, evidence distinguishing the benefits and barriers of adopting VR pedagogical methods to teach undergraduate nursing students is not well-defined in nursing literature.

PURPOSE

To identify current evidence on the benefits and barriers of adopting VR as a pedagogical method in nursing education.

METHODS

A scoping review of 6 databases using PRISMA-ScR reporting guidelines. Data were managed using Covidence® software. Table of Evidence illustrates the themes.

RESULTS

Seventeen articles identified 5 thematic benefits of VR (knowledge acquisition, student engagement, improved self-confidence, teaching strategy, and cost factors) and 4 barriers (physical discomfort, learning outcome challenges, challenges to integrating into curricula, and technology challenges).

CONCLUSIONS

VR is an effective teaching-learning strategy to reinforce nursing concepts and build competencies. It is not a substitute for clinical education.

Using Virtual Reality-Based Simulation in Neonatal Resuscitation Program Training

In this article, we investigate the incorporation of virtual reality (VR) into Neonatal Resuscitation Program (NRP) training. We describe the potential advantages and challenges of the use of VR with NRP. We compare conventional training approaches to VR-based simulation, reviewing diverse VR platforms and their specific roles in neonatal resuscitation education. In addition, technological and ethical aspects in medical training, current research, and prospective developments in this innovative educational tool are discussed.

Assessment of knowledge, attitude, and practice regarding medical waste management among operation room personnel in a tertiary hospital

Introduction

Medical waste management (MWM) is of concern to the medical and surgical communities in the hospital. Adequate knowledge, attitude, and practice regarding the management of healthcare waste are important for the proper handling and disposal by physicians and healthcare workers.

Objective

The aim of this study was an assessment of knowledge, attitude, and practices regarding medical waste management among operation room personnel in a tertiary hospital.

Methods

This study was a descriptive cross-sectional survey conducted at a single-center government Comprehensive Specialized Hospital operation room from 1-30 September 2022. All specialty operation room healthcare personnel consenting to cooperate and participate were included in the study. The data were collected using a self-administered questionnaire. The collected data were analyzed using SPSS. The results were presented in texts, tables and graphs.

Results

From 130 operation room personnel, the results revealed that the majority of the total respondents were male (83.1%). Only 30 (23.1%) of the respondents were involved in training, whereas 100 (76.9%) of the study participants have not participated in training. It was found that 86 (66.2%) of the respondents had good knowledge, 113 (86.9%) of the respondents had a good attitude, and 27 (20.8%) of the respondents had good practice.

Conclusion and recommendation

The authors' study reveals that the majority of study participants have a moderate level of knowledge, a good level of attitude, and poor levels of practice, according to Bloom's cut-off point. The institution should more fully implement the training for operation room personnel to improve their level of knowledge and practice of medical waste management.

Insights from explainable AI in oesophageal cancer team decisions

BACKGROUND

Clinician-led quality control into oncological decision-making is crucial for optimising patient care. Explainable artificial intelligence (XAI) techniques provide data-driven approaches to unravel how clinical variables influence this decision-making. We applied global XAI techniques to examine the impact of key clinical decision-drivers when mapped by a machine learning (ML) model, on the likelihood of receiving different oesophageal cancer (OC) treatment modalities by the multidisciplinary team (MDT).

METHODS

Retrospective analysis of 893 OC patients managed between 2010 and 2022 at our tertiary unit, used a random forests (RF) classifier to predict four possible treatment pathways as determined by the MDT: neoadjuvant chemotherapy followed by surgery (NACT + S), neoadjuvant chemoradiotherapy followed by surgery (NACRT + S), surgery-alone, and palliative management. Variable importance and partial dependence (PD) analyses then examined the influence of targeted high-ranking clinical variables within the ML model on treatment decisions as a surrogate model of the MDT decision-making dynamic.

RESULTS

Amongst guideline-variables known to determine treatments, such as Tumour-Node-Metastasis (TNM) staging, age also proved highly important to the RF model (16.1 % of total importance) on variable importance analysis. PD subsequently revealed that predicted probabilities for all treatment modalities change significantly after 75 years (p < 0.001). Likelihood of surgery-alone and palliative therapies increased for patients aged 75-85yrs but lowered for NACT/NACRT. Performance status divided patients into two clusters which influenced all predicted outcomes in conjunction with age.

CONCLUSION

XAI techniques delineate the relationship between clinical factors and OC treatment decisions. These techniques identify advanced age as heavily influencing decisions based on our model with a greater role in patients with specific tumour characteristics. This study methodology provides the means for exploring conscious/subconscious bias and interrogating inconsistencies in team-based decision-making within the era of AI-driven decision support.

Role of artificial intelligence, machine learning and deep learning models in corneal disorders - A narrative review

In the last decade, artificial intelligence (AI) has significantly impacted ophthalmology, particularly in managing corneal diseases, a major reversible cause of blindness. This review explores AI's transformative role in the corneal subspecialty, which has adopted advanced technology for superior clinical judgment, early diagnosis, and personalized therapy. While AI's role in anterior segment diseases is less documented compared to glaucoma and retinal pathologies, this review highlights its integration into corneal diagnostics through imaging techniques like slit-lamp biomicroscopy, anterior segment optical coherence tomography (AS-OCT), and in vivo confocal biomicroscopy. AI has been pivotal in refining decision-making and prognosis for conditions such as keratoconus, infectious keratitis, and dystrophies. Multi-disease deep learning neural networks (MDDNs) have shown diagnostic ability in classifying corneal diseases using AS-OCT images, achieving notable metrics like an AUC of 0.910. AI's progress over two decades has significantly improved the accuracy of diagnosing conditions like keratoconus and microbial keratitis. For instance, AI has achieved a 90.7% accuracy rate in classifying bacterial and fungal keratitis and an AUC of 0.910 in differentiating various corneal diseases. Convolutional neural networks (CNNs) have enhanced the analysis of color-coded corneal maps, yielding up to 99.3% diagnostic accuracy for keratoconus. Deep learning algorithms have also shown robust performance in detecting fungal hyphae on in vivo confocal microscopy, with precise quantification of hyphal density. AI models combining tomography scans and visual acuity have demonstrated up to 97% accuracy in keratoconus staging according to the Amsler-Krumeich classification. However, the review acknowledges the limitations of current AI models, including their reliance on binary classification, which may not capture the complexity of real-world clinical presentations with multiple coexisting disorders. Challenges also include dependency on data quality, diverse imaging protocols, and integrating multimodal images for a generalized AI diagnosis. The need for interpretability in AI models is emphasized to foster trust and applicability in clinical settings. Looking ahead, AI has the potential to unravel the intricate mechanisms behind corneal pathologies, reduce healthcare's carbon footprint, and revolutionize diagnostic and management paradigms. Ethical and regulatory considerations will accompany AI's clinical adoption, marking an era where AI not only assists but augments ophthalmic care.

Bibliometric analysis of artificial intelligence in healthcare research: Trends and future directions

Objective

The presence of artificial intelligence (AI) in healthcare is a powerful and game-changing force that is completely transforming the industry as a whole. Using sophisticated algorithms and data analytics, AI has unparalleled prospects for improving patient care, streamlining operational efficiency, and fostering innovation across the healthcare ecosystem. This study conducts a comprehensive bibliometric analysis of research on AI in healthcare, utilising the SCOPUS database as the primary data source.

Methods

Preliminary findings from 2013 identified 153 publications on AI and healthcare. Between 2019 and 2023, the number of publications increased exponentially, indicating significant growth and development in the field. The analysis employs various bibliometric indicators to assess research production performance, science mapping techniques, and thematic mapping analysis.

Results

The study reveals insights into research hotspots, thematic focus, and emerging trends in AI and healthcare research. Based on an extensive examination of the Scopus database provides a brief overview and suggests potential avenues for further investigation.

Conclusion

This article provides valuable contributions to understanding the current landscape of AI in healthcare, offering insights for future research directions and informing strategic decision making in the field.

Interdisciplinary Pain Board for Managing Patients with Palliative Care Needs and Substance Use Disorder: A Pilot Study

Context: Patients with cancer-related pain and concurrent substance use disorder (SUD) present a unique set of challenges for palliative care clinicians. A structured forum for interdisciplinary collaboration is needed to effectively manage this complex population. Objectives: Describe the feasibility and acceptability of a palliative care Complex Pain Board (CPB), an interdisciplinary team meeting to provide concrete care recommendations for patients with cancer-related pain and concurrent SUD and/or psychosocial complexity. Methods: We conducted a retrospective analysis of cases presented at CPB between May 2021 and June 2022 and a cross-sectional analysis of CBP participant surveys. Results: Among 28 cases included for analysis, gastrointestinal cancers (n = 7, 25.9%) and multiple myeloma (n = 5, 18.5%) were the most frequent cancer diagnoses. Primary reasons for referral were SUD (n = 22, 78.6%) and provider/team distress (n = 13, 46.4%). The most frequent recommendations made at CBP were encouraging interdisciplinary collaboration (n = 18, 64.3%), maintaining healthy boundaries (n = 15, 53.6%), and SUD management (n = 13, 46.4%). Of 14 scheduled meetings, most meetings involved the presentation of ≥1 cases (n = 12, 86%). Among 40 CBP participant surveys, most attendees (n = 38, 95%) were likely or highly likely to continue to attend. Conclusion: CPB is a feasible and acceptable intervention that allows for palliative care clinicians to collaborate and receive interdisciplinary team feedback and peer support on the management of patients with cancer-related pain and concurrent SUD and/or psychosocial complexity in the ambulatory care setting. Key Message: A regular, interdisciplinary team meeting (CPB) is a feasible and acceptable intervention to help palliative care clinicians manage challenging cases involving patients with cancer and concurrent SUD and/or psychosocial complexity.

The use of locum doctors in the NHS: understanding and improving the quality and safety of care

Background

The use of locum doctors in the National Health Service is widely believed to have increased, and there have been widespread and sustained concerns among policy-makers, healthcare providers, professional associations and professional regulators about the quality/safety, cost and effective use of locum doctors.

Objectives

To provide evidence on the extent, quality and safety of medical locum practice and the implications of medical locum working for health service organisation and delivery in primary and secondary care in the English National Health Service, to support policy and practice.

Design

Four interlinked work packages involving surveys of National Health Service trusts and of general practices in England; semistructured interviews and focus groups across 11 healthcare organisations in England; analysis of existing routine data sets on the medical workforce in primary care and in National Health Service trusts in England from National Health Service Digital and National Health Service Improvement; and analysis of data from the Clinical Practice Research Datalink in primary care and of electronic patient record data from two National Health Service hospitals in secondary care.

Results

In primary care, about 6% of general practice medical consultations were undertaken by locums in 2010 and this had risen slightly to about 7.1% in 2021. In National Health Service trusts (mostly secondary care and mental health), about 4.4% of medical staff full-time equivalent was provided by locum doctors. But those overall national rates of locum use hide a great deal of variation. In primary care, we found the National Health Service Digital workforce returns showed the rate of locum use by Clinical Commissioning Group varied from 1% to almost 31%. Among National Health Service trusts, the reported rate of locum use varied from < 1% to almost 16%. We found that there was poor awareness of and adherence to national guidance on locum working arrangements produced by National Health Service England. Our research showed that locum working can have adverse consequences for the quality and safety of care, but that such consequences were probably more likely to result from the organisational setting and the working arrangements than they were from the locum doctors themselves and their competence, clinical practice or behaviours.

Limitations

Our research was hampered in some respects by the COVID pandemic which both resulted in some delays and other challenges. Our efforts to use electronic patient record data in secondary care to explore locum doctor working were stymied by the problems of data access and quality.

Conclusions

Locum doctors are a key component of the medical workforce in the National Health Service, and provide necessary flexibility and additional capacity for healthcare organisations and services. We found that the extent of reliance on locum doctors varied considerably, but that an over-reliance on locums for service provision was undesirable. Some differences in practice and performance between locum and permanent doctors were found, but these seemed often to arise from organisational characteristics. We found that patients were more concerned with the clinical expertise and skills of the doctor they saw than whether they were a locum or not. Organisational arrangements for locum working could be improved in many respects.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR128349) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 37. See the NIHR Funding and Awards website for further award information.

Medical Image sharing: What do the public see when reviewing radiographs? A pilot study

INTRODUCTION

Policymakers wish to extend access to medical records, including medical imaging. Appreciating how patients might review radiographs could be key to establishing future training needs for healthcare professionals and how image sharing could be integrated into practice.

METHOD

A pilot study in the UK using a survey was distributed to adult participants via the online research platform Prolific. All subjects were without prior professional healthcare experience. Participants reviewed ten radiographs (single projection only) and were asked a two-stage question. Firstly, if the radiograph was 'normal' or 'abnormal' and secondly, if they had answered 'abnormal', to identify the abnormality from a pre-determined list featuring generic terms for pathologies.

RESULTS

Fifty participants completed the survey. A mean of 65.8 % of participants were able to correctly identify if radiographs were normal or abnormal. Results in relation to the identification of a pathology were not as positive, but still notable with a mean of 46.4 % correctly identifying abnormalities. Qualitative data demonstrated that members of the public are enthralled with reviewing radiographs and intrigued to understand their performance in identifying abnormalities.

CONCLUSION

In the pilot, members of the public could identify if a radiograph is normal or abnormal to a reasonable standard. Further detailed interpretation of images requires supportive intervention. This pilot study suggests that patients can participate in image sharing as part of their care. Image sharing may be beneficial to the therapeutic relationship, aiding patient understanding and enhancing consultations between healthcare professional and patient. Further research is indicated.

Impact of digital health on the quadruple aims of healthcare: A correlational and longitudinal study (Digimat Study)

BACKGROUND

Digital healthcare aims to deliver on the quadruple aim: enhance patient experiences, improve population health, reduce costs and improve provider experiences. Despite large investments, it is unclear how advancing digital health enables these healthcare aims.

OBJECTIVE

Our objectives were to: 1) measure the correlation between digital capability and health system outcomes mapped to the quadruple aim, and 2) measure the longitudinal impact of electronic medical record implementations upon health system outcomes.

MATERIALS AND METHODS

We undertook two studies: 1) Digital health correlational study investigating the association among healthcare system capability and healthcare aims, and 2) Digital hospital longitudinal study investigating outcomes pre and post electronic medical record implementation.

RESULTS

Digital health capability was associated with lower staff turnover. Digitising healthcare services was associated with decreased medication errors, decreased nosocomial infections, increased hospital activity, and a transient increase in staff leave.

DISCUSSION

These results suggest positive impacts on the population health and healthcare costs aim, minimal impacts on the provider experience aim and no observed impacts to the patient experience aim.

CONCLUSION

These findings should provide confidence to healthcare decision-makers investing in digital health.

Breast calcifications on mammography from systemic amyloidosis: A case report

Calcifications on mammography from systemic disease at times meet diagnostic criteria for histologic sampling to exclude malignancy. We present a case of bilateral groups of new calcifications on mammography that yielded amyloidosis on core biopsy. Awareness of our patient's known diagnosis of systemic light chain amyloidosis (AL) prompted use of Congo red staining to confirm the histologic diagnosis. Knowledge of systemic diseases with possible manifestations on mammography can facilitate cogent and clinically relevant radiology-pathology correlation.

Systematic Review and Meta-analysis of the Impact of Surgeon-Physician Co-management Models on Short Term Outcomes for Vascular Surgery Inpatients

OBJECTIVE

As the population ages, vascular surgeons are treating progressively older, multimorbid patients at risk of peri-operative complications. An embedded physician has been shown to improve outcomes in general and orthopaedic surgery. This systematic review and meta-analysis aimed to investigate the impact of surgeon-physician co-management models on morbidity and mortality rates in vascular inpatients.

DATA SOURCES

PubMed, Scopus, Embase, conference abstract listings, and clinical trial registries.

REVIEW METHODS

Studies comparing adult vascular surgery inpatients under co-management with standard of care were eligible. The relative risks (RRs) of death, medical complications, and 30 day re-admission between co-management and standard care were calculated. The effect of co-management on the mean length of stay was calculated using weighted means. Risk of bias was assessed using the Methodological Index for Non-Randomised Studies, and certainty assessment with the GRADE analysis tools.

RESULTS

No randomised controlled trials were identified. Eight single institution studies between 2011 and 2020 with 7 410 patients were included. All studies were observational using before-after methodology. Studies were of high to moderate risk of bias, and outcomes were of very low GRADE certainty of evidence. Co-management was associated with a statistically significant lower relative risk of death (RR 0.64, 95% confidence interval [CI] 0.44 - 0.92; p = .02), cardiac complications (RR 0.47, 95% CI 0.25 - 0.87; p = .02), and infective complications (RR 0.49, 95% CI 0.35 - 0.67; p < .001) in vascular inpatients. No statistically significant differences in length of stay (standard mean difference -0.6 days, 95% CI -1.44 - 0.24 days; p = .16) and 30 day re-admission (RR 0.96, 95% CI 0.84 - 1.08; p = .49) were noted.

CONCLUSION

Early results of physician and surgeon co-management for vascular surgery inpatients showed promising results from very low certainty data. Further well designed, prospective studies are needed to determine how to maximise the impact of physicians within a vascular service to improve patient outcomes while using hospital resources effectively.

A Fulbright International Exchange to Expand the Physician Assistant/Associate Curriculum in Geriatrics

ABSTRACT

The international growth of the physician assistant/associate (PA) profession provides opportunities for global exchange that PA faculty and clinicians should seek out and cultivate. Physician assistant/associate programs can benefit from the experiences and expertise of faculty educators from different backgrounds and countries. The Fulbright International Scholars Program is a well-established and recognized organization dedicated to supporting international exchange in higher education. This study describes the experience of an American PA who received a Fulbright Specialist Program award that provided the opportunity to collaborate with a Dutch PA program on improvement of their geriatric medicine didactic curriculum.